Medical image analysis centers on analyzing medical images to provide better health care and facilitate medical research, with special emphasis on efforts related to the applications of signal and image processing, computer vision, machine learning, and statistical analysis. Medical image analysis is critical to the advance of imaging-based medical research such as using magnetic resonance imaging to investigate brain anatomical and structural changes related to a disease process.

The main focus of this special issue will be emerging medical image analysis technologies and their application. We particularly take an interest in papers that focus on these topics: (1) detecting imaging-derived biomarkers for diagnosis and prognosis and (2) network analysis methods to model interactions among different components in disease processes, including brain structural and functional network analysis. Potential topics include, but are not limited to:

• Imaging biomarker detection
• Machine learning methods for imaging-based clinical decision support system
• Graph theoretical-based analysis methods
• Advanced medical image segmentation and registration
• Automatic and semiautomatic image analysis pipelines
• Information integration methods to process multimodality images
• Scalable algorithms to process massive image datasets
• Spatial and temporal modeling for medical image data

Before submission authors should carefully read over the journal’s Author Guidelines, which are located at http://www.hindawi.com/journals/cmmm/guidelines/. Prospective authors should submit an electronic copy of their complete manuscript through the journal Manuscript Tracking System at http://mts.hindawi.com/submit/journals/cmmm/mia/ according to the following timetable: